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ETL Frameworks
Transform Data in Your Warehouse
★ 4.9
Sheets to Data Warehouse Loader
★ 3.7
pip install dbt-corepip install gspreadpip install dbt-corepip install gspreadData engineers use dbt to manage all transformation logic inside the warehouse — writing SELECT statements as `.sql` model files that dbt compiles and runs in the right order. Python engineers also write custom dbt tests and macros in Python, and use dbt's Python models feature to run pandas or Spark logic alongside SQL in the same project.
Python data engineers use the `gspread` library to read business-owned datasets from Google Sheets into pandas DataFrames for pipeline processing. A common pattern is a weekly data feed maintained by a business team in Sheets — Python reads the latest values, validates them with Pydantic, transforms them, and loads them into the warehouse alongside operational data.
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